library(dataplumbr)
library(data.table)
wvs_anz_eto <- fread("../../data/dhs_link_char/working/wvs_anz_eto_deduplicated.csv")
unique_customers <- wvs_anz_eto[, .(unique_customers = .N)]
unique_anz <- wvs_anz_eto[ids %like% "anz" & (!ids %like% "eto") & (!ids %like% "wvs"), .(anz_only = .N)]
unique_eto <- wvs_anz_eto[ids %like% "eto" & (!ids %like% "anz") & (!ids %like% "wvs"), .(eto_only = .N)]
unique_wvs <- wvs_anz_eto[ids %like% "wvs" & (!ids %like% "anz") & (!ids %like% "eto"), .(wvs_only = .N)]
unique_eto_anz <- wvs_anz_eto[ids %like% "eto" & ids %like% "anz" & (!ids %like% "wvs"), .(eto_and_anz_only = .N)]
unique_eto_wvs <- wvs_anz_eto[ids %like% "eto" & ids %like% "wvs" & (!ids %like% "anz"), .(eto_and_wvs_only = .N)]
unique_wvs_anz <- wvs_anz_eto[ids %like% "wvs" & ids %like% "anz" & (!ids %like% "eto"), .(wvs_and_anz_only = .N)]
unique_wvs_anz_eto <- wvs_anz_eto[ids %like% "wvs" & ids %like% "anz" & ids %like% "eto", .(wvs_and_anz_and_eto = .N)]
anz_gender <- wvs_anz_eto[ids %like% "anz", .(datasource = "anz", .N), .(gender)][order(-N)]
wvs_gender <- wvs_anz_eto[ids %like% "wvs", .(datasource = "wvs", .N), .(gender)][order(-N)]
eto_gender <- wvs_anz_eto[ids %like% "eto", .(datasource = "eto", .N), .(gender)][order(-N)]
client_gender <- rbindlist(list(anz_gender, wvs_gender, eto_gender))
client_gender_grps <- client_gender[, .(dg = paste(datasource, gender), N), .(datasource, gender)]
anz_ethnic_id <- wvs_anz_eto[ids %like% "anz", .(datasource = "anz", .N), .(ethnic_id)][order(-N)]
wvs_ethnic_id <- wvs_anz_eto[ids %like% "wvs", .(datasource = "wvs", .N), .(ethnic_id)][order(-N)]
eto_ethnic_id <- wvs_anz_eto[ids %like% "eto", .(datasource = "eto", .N), .(ethnic_id)][order(-N)]
client_ethnic_id <- rbindlist(list(anz_ethnic_id, wvs_ethnic_id, eto_ethnic_id))
client_ethnic_id[ethnic_id=="" | is.null(ethnic_id) | is.na(ethnic_id), ethnic_id := "no value"]
client_ethnic_id_grps <- client_ethnic_id[, .(de = paste(datasource, ethnic_id), N), .(datasource, ethnic_id)]
library(plotly)
e <- plot_ly(data= anz_ethnic_id,
labels = ~ethnic_id,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for Anasazi',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
g <- plot_ly(data=anz_gender,
labels = ~gender,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for Anasazi',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
library(plotly)
e <- plot_ly(data= wvs_ethnic_id,
labels = ~ethnic_id,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for Web Vision',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
g <- plot_ly(data=wvs_gender,
labels = ~gender,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for Web Vision',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
e <- plot_ly(data= eto_ethnic_id,
labels = ~ethnic_id,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
e <- layout(e, title = 'Ethnic Id Breakdown for ETO',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
g <- plot_ly(data=eto_gender,
labels = ~gender,
values = ~N,
type = 'pie',
textposition = 'inside',
textinfo = 'label+percent')
g <- layout(g, title = 'Gender Breakdown for ETO',
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))